AI and Cyber Insurance: The Challenges of Underwriting Emerging Technologies

AI and Cyber Insurance: The Challenges of Underwriting Emerging Technologies

In the rapidly changing technological environment, artificial intelligence has become one of the most profound innovations. With its help, many companies have managed to revolutionize their work processes and achieve spectacular results. However, AI is a double-edged sword, and with the opportunities it provides comes the risk, especially in terms of insurance. The article will explore the situation in the environment of AI and cyber insurance, highlighting the problems that insurance companies may face and possible examples.

The Convergence of AI and Cybersecurity

Several advantages provided by the potential use of AI in cybersecurity are especially helpful. First of all, AI allows increased protection and facilitates security operations, detecting possible breaches, and reacting on time. However, in addition to these benefits, AI introduces some new flaws as well. One of the plausible cases is that AI systems might be attacked or tampered with. In such a way, it is possible to deceive machine learning models by attacks and make them make wrong decisions leading to insecurity.

Quantifying the Risk

One of the first problems that insurance agents are likely to face is that the risk is complicated to quantify. Insurers have little data on the majority of developed systems and a low level of information about actuarial data for AI in general. The information they have about historical risks and the results of future research is also uncertain and should be interpreted with caution. In such a way, the companies that perform insurance operations have to rely on the opinion of experts and actuarial modeling that can result in different levels of pessimism in relation to the outcomes.

Policy Coverage and Exclusions

The limitation for actuaries is that they usually have to know about possible risks before the policy is concluded, but with emerging technologies, it is not always the case. In other words, it is possible to model only a small percentage of possible scenarios of AI use and define the level of probability. Neither actuaries nor insurers have enough information on the risks of AI systems used in new applications. There are also moral hazard conditions if insurers try to save on the payment of AI insurance, which means their distribution will necessarily be limited.

Regulatory Considerations

The current regulatory environment for AI and cyber insurance is a combination of both national and international guidelines. These regulations are not uniform across all jurisdictions and insurers must be aware of this multi-jurisdiction regulatory framework in their risk assessments.


One of the critical questions that underwriting AI insurance or cyber insurance pose is the question of reinsuring these risks. Reinsurance is a standard method to spread out the risk over numerous parties. The significant advantage of reinsurance in the case of AI and cyber insurance is its ability to mitigate the impact of catastrophic AI-related cyber events. However, predictive and deep learning models are inherently harder to assess and reinsurers have to be careful in taking these risks, demanding full transparency and comprehensive risk assessment of the primary insurer.

Educating Stakeholders

Providing knowledge and risk assessment tools to stakeholders is vital both to the success of underwriting and the overall risk assessment of the industry. AI and cyber insurance underwriting is no exception – on the one hand, primary insurers have to educate their clients on the risks associated with AI systems and the dangers presented by the lack of adequate cybersecurity measures. On the other hand, insurers have to educate themselves, constantly updating their knowledge on applications of AI in order to accurately assess the risk.


The intersection of AI and cyber insurance presents both an opportunity and a challenge to the industry. These risks, if assessed accurately and managed adequately, could allow insurance companies to lead in the market development. As the AI and the broader tech sector develop, the insurance reaction and risk assessment abilities should also develop with new tools. Assessing AI through its testing is not enough – its future developments are still unknown. As such, a complex risk assessment strategy is needed to solve AI and cyber insurance.

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